Embodiments of the invention relate generally to a system and method for depth from defocus imaging, and more particularly to a contactless multi-fingerprint collection device.
It is well known that the patterns and geometry of fingerprints are different for each individual and are unchanged over time. Thus fingerprints serve as extremely accurate identifiers of an individual since they rely on un-modifiable physical attributes. The classification of fingerprints is usually based on certain characteristics such as arch, loop or whorl, with the most distinctive characteristics being the minutiae, the forks, or endings found in the ridges and the overall shape of the ridge flow.
Traditionally, fingerprints have been obtained by means of ink and paper, where a subject covers a surface of their finger with ink and presses/rolls their finger onto paper or a similar surface to produce a rolled fingerprint. More recently, various electronic fingerprint scanning systems have been developed that obtain images of fingerprints utilizing an optical fingerprint image capture technique. Such electronic fingerprint scanning systems have typically been in the form of contact based fingerprint readers that require a subject's finger to be put in contact with a screen and then physically rolled across the screen to provide an optically acquired full rolled-image fingerprint. However, contact-based fingerprint readers have significant drawbacks associated therewith. For example, in a field environment, dirt, grease or other debris may build up on the window of contact based fingerprint readers, so as to generate poor quality fingerprint images. Additionally, such contact-based fingerprint readers provide a means of spreading disease or other contamination from one person to another.
In recent electronic fingerprint scanning systems, contactless fingerprint readers capture fingerprints without the need for physical contact between a subject's finger and a screen. The goal is to generate a rolled equivalent fingerprint image using a contactless imaging system in which images are formed by a lens. Conventional imaging provides 2D representation of the object, whereas to generate the rolled equivalent fingerprint, one requires the 3D profile of the finger. For an object such as a finger, some parts of the object are in focus and some are defocused when imaged with a shallow depth of field imaging system. Typically, an in-focus region is a region of an object that is in as sharp as possible focus, and conversely defocus refers to a lack of focus, the degree of which can be calculated between two images. Known systems may generate a depth map of the object using either a depth from focus (DFF) or a depth from defocus (DFD) algorithm.
In one system, a contactless fingerprint scanning system acquires an image of the finger by utilizing a structured light source, and a 3D image is generated using a DFF algorithm. In a DFF algorithm, as an example, many measurements are made at various focal plane positions and the many measurements are used to generate a depth map. Typically, the various focal plane positions are obtained by either physical movement of the object or lens, or by adjustment of the focal plane (using known techniques or using one or more birefringent lenses producing focal shifts at different polarization angles passing therethrough). DFF-based systems, however, typically require many measurements to be obtained and also may include adjustment of the focal plane to focus on the object, as well as a structured light source.
For a given object, the amount of defocus depends on at least two parameters: 1) a distance of the object to the lens, and 2) the lens characteristics. If the second parameter (i.e., the lens characteristics) is known, and the system can accurately measure an amount of defocus, then the object distance can be determined. Such forms the basis of known DFD algorithms.
Thus, in some contactless finger print readers, the system acquires an image of the finger by utilizing a white light source, and a 3D image is generated using a DFD algorithm. In a DFD algorithm, a defocus function acts as a convoluting kernel with the fingerprint, and the most direct way to recover it is through the frequency domain analysis of obtained image patches. Essentially, as the amount of defocus increases, the convolving kernel's width decreases, resulting in elimination of high frequency content.
DFD algorithms typically start with an assumption of a simplified Gaussian or pillbox estimator for a point spread function (PSF), building up on a polychromatic illumination assumption. Typically, an object point, when imaged, will look like a bell curve rather than a sharp point. The function describing the shape of the bell curves is called the ‘PSF’, and the shape of the PSF on an image detector depends on the distance of the object point to the lens, as well as internal lens characteristics. Thus, these assumptions simplify the mathematical derivations and provide a convenient approach to DFD. The extent to which such assumptions hold depends on the particular imaging system and illumination condition. For highly corrected imaging optics and white light illumination, the PSF resembles a Gaussian or a pillbox and assuming so typically generates a depth estimator with a reasonable error. However, it can be shown that depth estimation based on DFD is highly sensitive to proper determination of PSF structure, and applying DFD based on Gaussian (or pillbox) PSF models to an imaging system where PSF departs from this assumption results in unreliable depth estimates. That is, the simplified model does not adequately describe physical lens behavior when there is a high degree of aberration, when a lens has a small depth-of-field compared to object size, when quasi-monochromatic light is used (such as an LED), or when monochromatic light is used (such as a laser), as examples. Thus, known DFD systems fail to estimate object distance and fail to accurately reproduce a fingerprint in a contactless system.
Therefore, it would be desirable to design a system and method of acquiring fingerprints in a contactless application that accounts for lens imperfections.